Chensyfighting

Chensyfighting's Stars

• zhanwen/MathModel

  研究生数学建模，本科生数学建模、数学建模竞赛优秀论文，数学建模算法，LaTeX论文模板，算法思维导图，参考书籍，Matlab软件教程，PPT

  Language:TeX7.8k2.1k

• Lizhi-sjtu/DRL-code-pytorch

  Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.

  Language:Python998169

• caichao/AcuTe

  We develop an acoustic thermometer empowered by a single smartphone

  Language:Java115

• Jingliang-Duan/DSAC-T

  DSAC-v2; DASC; Distributional Soft Actor-Critic

  Language:Python20319

• smoggy-P/MPC-Collision-Avoidance

  Implementation of MPC to solve collision avoidance problem for 3D drone

  Language:Jupyter Notebook12

• uzh-rpg/flightmare

  An Open Flexible Quadrotor Simulator

  Language:C++968340

• MyRepositories-hub/Simple-Policy-Optimization

  Language:Python332

• openai/gym

  A toolkit for developing and comparing reinforcement learning algorithms.

  Language:Python34.4k8.6k

• XinJingHao/DRL-Pytorch

  Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

  Language:Python1.1k131

• openai/baselines

  OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

  Language:Python15.6k4.9k

• sfujim/TD3

  Author's PyTorch implementation of TD3 for OpenAI gym tasks

  Language:Python1.7k434

• twni2016/pomdp-baselines

  Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022

  Language:Python28841

• qlt315/UCMEC-mmWave-Fronthaul

  Simulation code of our paper in IEEE Transactions on Mobile Computing: ''Towards Decentralized Task Offloading and Resource Allocation in User-Centric Mobile Edge Computing''

  Language:Python635

• agi-brain/xuance

  XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

  Language:Python56098

• yoshitomo-matsubara/torchdistill

  A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.

  Language:Python1.3k131